The proposed research investigates how health affects friend selection behavior in adolescent social networks. Prior research has documented numerous pathways through which relationships affect individual health and well-being. For instance, social networks offer support to buffer the impact of stress on health, reinforce health-related behavior, and serve as the infrastructure for disease transmission. Yet despite the importance of social network factors for health, research has rarely examined how adolescents acquire their respective network positions. The literatures on social networks in sociology and the developmental and ecological perspectives from psychology both inform the processes at hand, but have rarely been integrated. In integrating these two perspectives, the current research advances the field by testing several new hypothesized mechanisms by which health may affect the friend selection process. Our first aim is to explain the common tendency for individuals in poor health to associate with one another. Such relationships can exacerbate health conditions through the absence of social support and by reinforcing unhealthy behavior. Second, we aim to identify individual attributes that lead adolescents to select friends whose behavior is more unhealthy than their own. Identifying these adolescents and potential mechanisms is vital as these new friendships often reposition adolescents on a worse life course trajectory. Our third aim is to test whether the preceding effects are moderated by involvement in extracurricular activities, which, by promoting friendships, should dampen the negative effects of poor health on friend selection. We investigate these aims using data from the National Longitudinal Study of Adolescent Health and two cutting-edge statistical models: the Exponential Random Graph Model (ERGM) and the Stochastic Actor Based (SAB) model. The results of the proposed research will lay the groundwork for developing more comprehensive and ecologically-valid theoretical models of the intersection between health and social networks to inform future interventions. Our ultimate goal is to understand the processes through which health and social networks mutually affect one another, with long-term consequences for health outcomes.